Users are often required to log into various networks, accounts, services, portals, websites, applications, and other environments. Fraudulent users may be capable of obtaining a user's log-in information (e.g., username and password) for a given environment and entering the log-in information quickly and with a high degree of accuracy, such as by employing a bot or script to automatically enter log-in information for one or more users. For example, a fraudulent user may enter log-in information quickly and error-free, such as by copying and pasting the log-in information, whereas a legitimate user may manually enter the log-in information, which can be comparatively time consuming and carry a comparatively high likelihood of error during entry. To counter such fraudulent activity, there exist methods of tracking so-called behavioral biometrics of a user. As opposed to simply determining what data is entered (e.g., determining whether a proffered password is correct), behavioral biometrics refers to determining how the data is entered, such as by monitoring keystroke dynamics.
Existing systems may analyze data being inputted by a user into a computing device as the user attempts to access an environment. The inputted data is often compared to a stored user profile to determine whether the inputted data is indicative of the user in question inputting the data. Existing systems may determine a similarity score of the inputted data to the stored user profile, and if the similarity score is above a predetermined threshold, the user's behavioral biometrics may be considered authenticated, such that if the user entered the correct log-in information, the user is granted access to the environment. If the score is below the predetermined threshold, the user's session in the environment may be flagged for additional security methods, such as some other form of secondary user authentication. Alternately, the user may be refused access to the environment unless the correct behavioral biometric data is provided or some other secondary user authentication is completed.
Existing systems, however, may not accurately accommodate scenarios in which a user switches between manually entering log-in information and using a password manager or some other form of automated log-in information entry. In addition, behavioral biometric data for a user may vary based on the type of computing device used by the user, and existing systems may not accurately accommodate scenarios in which a user switches between different computing devices and/or different types of computing devices. Moreover, behavioral biometric data for a user using a given computing device may vary based on the physical position of a user. For example, behavioral biometric data associated with a user entering log-in information on a mobile phone while the user is in a prone position may be substantially different from behavioral biometric data associated with the same user entering the same log-in information on the same mobile phone while the user is in a standing position, and behavioral biometric data associated with the same user entering the same log-in information on the same mobile phone while the user is in a seated position may be different still. As another example, behavioral biometric data associated with a user entering log-in information on a laptop computer while the user is in a seated position may be different from behavioral biometric data associated with the same user entering the same log-in information on the same laptop computer while the user is lying down.